By combining immune monitoring on multiple platforms in a single center, the Human Immune Monitoring Center (HIMC) has created an ideal environment for standardization, technology development, and data mining related to immune monitoring. Over the last few year's, we have built an array of high-throughput and high-content assays that are proving useful for a variety of immunological studies. The Scientific Core B will provide standardized immunological assays across studies within this proposed U19 project, focusing especially on the characterization of key populations of blood leukocytes, particularly B cells, T cells, and basophils, in patients with peanut allergy (PA) as they undergo treatment with oral immunotherapy (OIT) or placebo, as well as work with individual projects to develop additional novel immune monitoring assays. The specific aims are: 1. To provide standardized immune monitoring assays across projects. These will include detailed immunophenotyping of whole blood by mass cytometry (CyTOF), as well as phosphoepitope flow cytometry. By using the same standardized assays across all cohorts, we will greatly increase the power to test hypotheses related to any of the readouts of these assays. 2. To develop novel immune monitoring assays with individual projects. We will work with Project 3 on applications of MHC class ll-peptide multimer assays. These will be used in conjunction with microfluidic qPCR arrays, for comprehensive assessment of individual epitope-specific T cells. We will also develop phosphoepitope flow cytometry panels on the CyTOF mass cytometry platform. Once optimized, these technologies will be made available to other projects to create larger standardized data sets. 3. To facilitate mining of immune monitoring data. We will continue to expand our data integration and mining tool, Stanford Data Miner (SDM), for use with standard assays generated in this U19. We can also use SDM to compare U19 data with data generated with the same standardized assays in unrelated projects. We will work with the Data Management and Analysis Core A to mine those data using bioinformatics tools.